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Found 15 Skills
GPU-accelerated frame extraction for Movie_F dashcam videos. This skill should be used when the user needs to extract frames from Movie_F category dashcam videos placed in the Desktop CARDV folder. Extracts 3 frames per video (BEGIN, MIDDLE, END) using NVIDIA CUDA acceleration with automatic gap analysis, parallel processing, and strict error handling. This is specifically designed for Movie_F category only.
Automatically analyze Bilibili video content, download videos and split them into frame images, use AI to analyze and generate detailed thematic documents or practical tutorials.
Search GIF providers with CLI/TUI, download results, and extract stills/sheets.
Adds visual descriptions to transcripts by extracting and analyzing video frames with ffmpeg. Creates visual transcript with periodic visual descriptions of the video clip. Use when all files have audio transcripts present (transcript) but don't yet have visual transcripts created (visual_transcript).
This skill should be used when analyzing video files. Claude cannot process video directly, so this skill extracts frames hierarchically - starting with a quick overview, then zooming into regions of interest with higher resolution and temporal density. Use when asked to watch, analyze, review, or understand video content.
Extract frames from videos at specific timestamps or intervals, find best frames, and generate thumbnail grids for previews.
Analyze animated GIF files by extracting and viewing frames as sequential video. Use when: - User mentions a GIF file path (e.g., "./demo.gif", "~/Downloads/animation.gif") - User wants to analyze or understand a GIF animation - User asks about motion, changes, or content in a GIF - User attaches or references a .gif file for analysis - User wants to examine a screen recording in GIF format - User invokes /gif slash command Keywords: "GIF", ".gif", "animation", "animated", "frames", "screen recording", "analyze gif", "gif analysis", "view gif", "gif content", "gif motion" Trigger patterns: - Natural language: "Analyze this GIF: ./demo.gif" - Slash command: `/gif <path>` or `/gif <path> <message>` When triggered, extract frames using the Python script, view frames in order, and interpret as continuous video sequence.
Understand video content locally using ffmpeg frame extraction and Whisper transcription. No API keys needed. Use when: (1) Understanding what a video contains, (2) Transcribing video audio locally, (3) Extracting key frames for visual analysis, (4) Getting video content without API keys.
Production-grade video frame extraction with thumbnail grids, GIF creation, and batch frame processing. Includes intelligent quality presets, progress tracking, and comprehensive error handling.
Extract frames or short clips from videos using ffmpeg.
Extracts frames at regular intervals from dashcam videos to create compact visual summaries of vehicle movement and location changes. This skill should be used when users need motion trajectory analysis, want to optimize dashcam storage by 90%+, need quick visual review of hours of footage, or want to create visual timelines of trips.
Extract frames from video files using ffmpeg for AI/LLM analysis. Use when (1) the user asks to analyze, describe, or summarize a video file, (2) the user wants to extract frames or screenshots from a video, (3) the user provides a video file (.mp4, .mov, .avi, .mkv, .webm, etc.) and asks questions about its visual content, (4) the user wants to identify scenes, objects, or events in a video, (5) the user wants timestamps overlaid on extracted frames for temporal reference. Converts video into JPEG frames that can be attached to LLM prompts as images. Requires ffmpeg on PATH. Supports scene-change detection, model-aware optimization (Claude/OpenAI/Gemini), quality presets (efficient/balanced/detailed/ocr), grayscale and high-contrast OCR mode, and automatic FPS calculation via --max-frames.